应用地震属性与测井数据反演储层参数
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摘要
通过分析其他类地震属性特征提取 ,研究了适合于地震信号小波变换的基本小波。提取地震记录的小波变换系数及其频谱属性 ,并对提取的各类地震属性进行组合、优化研究。利用BP神经网络建立测井声波时差和地震属性的非线性映射关系 ,进行声波时差外推反演。对研究区的所有井的外推反演结果 ,采用距离加权平均 ,得到最终的反演声波时差结果。最后利用反演的声波时差资料计算孔隙度参数。经已知井和新钻井验证 ,计算结果和实际情况相一致 ,效果令人满意
After extraction of seismic attributes, the base wavelet of wavelet transform was derived, and wavelet coefficients and their Fourier spectral are calculated. Seismic attributes were then optimized. By means of BP neural network, the nonlinear relation between seismic attributes and interval transit time (Δt) was established, and seismic data inversion was carried out. The total Δt in the survey area was obtained by distance weighted average of the extrapolation of inversion results in different wells. Porosity was calculated with the resulted Δt.The resulted porosity is in good agreement with the ones in wells.
After extraction of seismic attributes, the base wavelet of wavelet transform was derived, and wavelet coefficients and their Fourier spectral are calculated. Seismic attributes were then optimized. By means of BP neural network, the nonlinear relation between seismic attributes and interval transit time (Δt) was established, and seismic data inversion was carried out. The total Δt in the survey area was obtained by distance weighted average of the extrapolation of inversion results in different wells. Porosity was calculated with the resulted Δt.The resulted porosity is in good agreement with the ones in wells.
引文
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5 李建平.小波分析与信号处理[M].重庆:重庆出版社,1997.56～89
2 陈遵德.储层地震属性优化方法[M].北京:石油工业出版社,1998.34～134
3 宋维琪,仝兆岐.惠民凹陷江家店地区隐蔽油藏预测[J].石油勘探与开发,2000,27(6):124～128
4 楼顺天,施阳.基于MATLAB的系统分析与设计———神经网络[M].西安:西安电子科技大学出版社,2000.67～98
5 李建平.小波分析与信号处理[M].重庆:重庆出版社,1997.56～89
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